Data Analyst Course in Dubai

12 immersive modules & professional capstone projects

Comprehensive Data Analytics & AI-Enhanced Reporting Program

60 hours of AI integration training

Copilot & Automation Sandbox for work efficiency

Flexible learning modes & easy payment options

4.85/5

5568 Enrolled

Overview

Our Data Analyst course helps professionals in the following ways:

Covers data analysis across Excel, SQL, Power BI, and Python
Builds Power BI proficiency through DAX, data modelling, and Power BI Service
Introduces AI-driven analytics using Microsoft Copilot and Fabric within Power BI
Develops Python skills through Pandas, NumPy, and Jupyter for data handling tasks
Applies statistical methods, including probability, hypothesis testing, and inference

Learning objectives

Successful completion of our training will help professionals in the following ways:

Apply advanced Excel functions and PivotTables to analyse and report business data

Write SQL queries to extract, filter, and manipulate data from relational databases

Build Power BI dashboards using DAX measures, data modelling, and calculated columns

Use Microsoft Copilot and Fabric to support predictive analytics and automated reporting

Conduct hypothesis testing and A/B testing to support evidence-based business decisions

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Our Trainers

Learners Point has a reputation for high-quality training that makes a difference in people's lives. We undertake a practical and innovative approach to working closely with businesses to improve their workforce. Our expertise is wide-ranging with ample support from our expert trainers who are globally recognized and hold a diverse set of experiences in their field of expertise. We are proud of our instructors who take ownership of our distinctive and comprehensive training methodologies, help our students imbibe those with ease, and accomplish gracefully.

We at Learners Point believe in encouraging our students to embark upon a journey of lifelong learning and self-development, with the aid of our comprehensive and distinctive courses tailored to current market trends. The manifestation of our career-oriented approach is what we assure through a pleasant professional enriched environment with cutting-edge technology, and an outstanding while highly acknowledged training staff that uses up-to-date methodologies and quality course material. With our aim to mold professionals to be future leaders, our industry expert trainers provide the best in town mentorship to our students while endowing them with the thirst for knowledge and inspiring them to strive for professional and human excellence.

KHDA Certificate

Earn a KHDA attested Course Certificate. The Knowledge and Human Development Authority (KHDA) is the educational quality assurance and regulatory authority of the Government of Dubai, United Arab Emirates.

Learners Point Certificate

Earn a Course Completion Certificate, an official Learners Point credential that confirms that you have successfully completed a course with us.

Related courses

Curriculum

Introduction to Python and Jupyter Notebooks
Variables, data types, and control flow
Functions and libraries in Python
Working with data (Lists, Tuples, Dictionaries)
Data structures and algorithms basics

Industry Simulation – Module 1:

Project Name: Data Processing Automation
Description: Automate report filtering tasks using Python to process raw business data, demonstrating basic Python syntax and data manipulation techniques.

Introduction to Excel for business analysis
Using formulas and functions for data manipulation
Advanced Excel functionalities
PivotTables, charts, and graphs for reporting
Data cleaning and visualization with Excel

Industry Simulation – Module 2:

Project Name: Business Data Report Generation
Description: Use Excel to analyze business data, generate key reports, and visualize the outcomes for decision-making

Introduction to SQL and basic queries
Filtering and sorting data
Joins (INNER JOIN, LEFT JOIN, etc.)
Aggregating data using GROUP BY and HAVING
Subqueries and set operations

Industry Simulation – Module 3:

Project Name: SQL Query for Sales Data Analysis
Description: Write SQL queries to extract and manipulate sales data for analysis, preparing it for further insights and reporting.

Getting started with Power BI Desktop
Importing data from Excel, SQL, and other sources
Creating basic visualizations (charts, graphs, tables)
Building a simple report
Using filters, slicers, and hierarchies

Industry Simulation – Module 4:

Project Name: Power BI Sales Dashboard
Description: Create a basic Power BI dashboard visualizing key sales metrics like total sales, sales by region, and monthly trends.

Data modeling basics in Power BI
Introduction to DAX (Data Analysis Expressions)
Building calculated columns and measures
Aggregating data using DAX
Creating more advanced visualizations using DAX

Industry Simulation – Module 5:

Project Name: Sales Reporting with DAX
Description: Use DAX in Power BI to create calculated columns and measures, building a comprehensive sales report.

Designing and sharing advanced visuals
Working with Power BI Servic
Publishing reports and dashboards to the cloud
Collaborating with team members in Power BI Service
Creating interactive reports

Industry Simulation – Module 6:

Project Name: Interactive Sales Dashboard
Description: Design and share an interactive sales dashboard in Power BI, integrating data from multiple sources

AI-powered features in Power BI
Using Copilot in Power BI
Dataflow management with Microsoft Fabric
Predictive analytics and forecasting
Best practices for AI-driven analytics in Power BI

Industry Simulation – Module 7:

Project Name: AI-Powered Analytics Implementation
Description: Implement AI-powered features in Power BI, leveraging Copilot and Microsoft Fabric for real-time data integration and predictive analytics.

Advanced data analysis with Python libraries (Pandas, NumPy, etc.)
Exploratory data analysis (EDA) techniques
Handling missing data and outliers
Data transformations and aggregations

Industry Simulation – Module 8:

Project Name: Automated Data Cleaning in Python
Description: Use Python to clean, transform, and analyze datasets, automating the data preparation process for further analysis.

NumPy for numerical computations
Jupyter for interactive data analysis
Matrix operations and linear algebra in NumPy
Handling large datasets with NumPy

Industry Simulation – Module 9:

Project Name: Data Exploration with NumPy
Description: Explore a large dataset using NumPy and Jupyter for data analysis, highlighting key insights and trends.

Dataframes in Pandas
Data wrangling and cleaning
Merging, reshaping, and slicing data
Groupby and aggregation techniques

Industry Simulation – Module 10:

Project Name: Data Cleaning & Transformation with Pandas
Description: Use Pandas to clean, manipulate, and merge data, preparing it for analysis and visualization.

Basic statistical analysis with Pandas
Probability distributions
Statistical inference
Hypothesis testing techniques

Industry Simulation – Module 11:

Project Name: Statistical Analysis of Business Data
Description: Perform statistical analysis on a business dataset, calculating key metrics like mean, median, variance, and standard deviation.

A/B testing and significance testing
Confidence intervals and p-values
Statistical power and effect size
Practical applications in business decision-making

Industry Simulation – Module 12:

Project Name: A/B Testing for E-commerce
Description: Conduct an A/B test for an e-commerce business and evaluate the results using t-tests and confidence intervals.

Project Name: Integrated Data Analysis & Reporting Solution
Objective: Participants will apply all learned skills by analyzing a dataset and building a comprehensive business report or dashboard that integrates data manipulation, visualization, and predictive modeling

Project Name: AI-Powered Reporting Tool
Description: Design an AI-powered reporting tool that automates data extraction and analysis, integrating Power BI and Tableau for dynamic reporting.

Project Name: AI-Enhanced Data Analysis for Business Applications
Description: Simulate data analysis tasks relevant to domains like finance, marketing, operations, etc., using AI-powered tools for business insight generation.

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Frequently asked questions

Data Analysts play a crucial role in today’s data-driven world, helping businesses make informed decisions based on data insights. Their job involves collecting, processing, and analysing large data sets to identify patterns, trends, and valuable insights that support strategic business decisions.

One of the key responsibilities of a data analyst is data mining, which includes gathering data from different sources, cleaning and organizing it to ensure accuracy, and preparing it for analysis.

The training is designed for:

Junior and Mid-Level Managers
Finance Professional
Operations Executive
Marketing Analyst
Anyone whose role regularly involves reporting or data-driven decision-making

Professionals do not need a programming or engineering background to enrol in the program; those with basic Excel or spreadsheet knowledge can join with ease. The course is structured to build skills in a logical sequence, starting with the fundamentals of Excel and Python before advancing to SQL, Power BI, and statistical inference.

The job market in Dubai and the broader UAE demonstrates a steady demand for professionals skilled in structured data tools, particularly in sectors such as finance, logistics, retail, and technology. Common roles in these fields include:

Data Analyst
Business Intelligence Analyst
Reporting Analyst
Data Operations Specialist

Employers in the region now expect analysts to manage complete workflows, including querying databases, cleaning datasets, publishing dashboards, and applying statistical reasoning instead of limiting their work to just one tool.

Learners Point offers a Data Analyst Training Course in Dubai through instructor-led sessions that emphasise practical learning. The course consists of 12 modules, each featuring an industry simulation project based on realistic business scenarios rather than theoretical exercises.

At the end of the program, professionals will complete a comprehensive capstone project that requires them to integrate all the tools and methods learned throughout the course. The sessions are designed to accommodate working professionals and provide a logical progression across topics, ensuring that each subject is connected rather than treated in isolation.

The Data Analyst Training Course is tailored for professionals who come from non-technical backgrounds. It begins with the basics of Python and Excel to help build foundational confidence. After that, the curriculum covers SQL, Power BI, and statistical methods. Many professionals working in finance, HR, operations, or marketing have found thecourse content directly applicable to their current roles.

The program assumes that participants have a professional background and are willing to engage in structured practice, but no prior experience in programming or database management is required.

The training provides UAE professionals with a structured, verifiable record of proficiency in essential tools. It emphasises practical skills in Power BI, SQL, and Python, which are the primary competencies employers evaluate during the hiring process.

In a competitive job market where many claim analytical experience but often lack concrete evidence, certification helps establish credibility in hiring discussions and conversations on internal promotions. Additionally, it benefits professionals remove already working with data informally, as it offers a structured framework to solidify their existing knowledge and identify any gaps.

A Data Analyst Course with AI integration goes beyond the regular study of Excel, SQL, Power BI, Python, and data visualisation. It teaches participants how to use AI tools such as Copilot to analyse data faster, identify patterns, generate summaries, improve reporting workflows, and support business decision-making with greater efficiency.

A regular Data Analyst Course usually focuses on manual data cleaning, dashboard creation, statistical analysis, and reporting. However, AI-integrated training adds practical exposure to AI-assisted analytics, automated reporting, prompt-based analysis, and smart dashboard interpretation.